The previous two posts focused on getting a server up and running, and setting up your server with user access. In this post, we finally work on installing R and RStudio Server on our instance and configuring the application. Pay special attention to the packages notes at the end of this post. This will ensure a significantly decreased number of headaches. Let’s go! Continue reading…

The previous post focused on the initial task of instantiating a server. We chose Digital Ocean because it has an easy-to-use interface, great pricing, and great customer support. I should note that you can use any cloud service you’d like, so long as you can install Ubuntu 14.04 on it. If you do choose Digital Ocean, get $10 credit to your account by signing up with this link. In this post, we’ll focus on some basic steps to secure your server and ensure proper configuration. These steps are taken from Digital Ocean’s tutorial pages, though slightly modified to suit the use case. Let’s get started! Note that this tutorial focuses on mac users, which already have ssh console access through Terminal. Windows users can follow along, though you’ll need to install and configurePuTTY beforehand. Continue reading…

There are many advantages to moving away from local data analysis and pushing it to the cloud. I’ve talked a little bit about them here. This post, however, isn’t intended to convince you even more. I’m hoping that you’re already convinced. And if you are, see below a complete tutorial of what I believe to be the quickest way to get up and running with R in the cloud. Continue reading…